bioRxivImmunologyPreprint
Spectrum of Opportunistic Disease and Associated Factors among Patients Attending ART Clinic, Nekemte Specialized Hospital, Western Ethiopia
Abstract
IntroductionHuman immunodeficiency virus (HIV), the causal agent for Acquired I Immunodeficiency Syndrome (AIDS) is the worlds greatest severe public health and development contest. Since the beginning of the epidemic, 38 million of people are living with HIV/AIDS and 1.7 million people newly infected with HIV. Increased availability and accessibility of ART has essentially improved the survival rate, through lowering the incidence of OIs among peoples living with HIV/AIDS. Risk of developing Opportunistic infections in HIV patients depend on experience to potential pathogens, virulence of pathogens, degree of host immunity and the use of antimicrobial prophylaxis. In Ethiopia, however remarkable decline of new infection (81%) for decades, since 2008 HIV incidence rate began to rise by 10% and number of new infection diagnosed each year increased by 36% among all ages and doubled among adult. There is a limited studies describing the spectrum of opportunistic infection and associated factors in the study settings. Therefore, this study was aimed to determine the spectrum of Opportunistic infections in the study area. MethodsA Facility based retrospective cross-sectional study was employed from 2015-2019 G.C. The sample size was computed using single population proportion formula. Accordingly, four hundred ninety seven (497) medical records of study participants were reviewed. Simple random sampling technique was used to select the participants included in this study. Data were extracted from the ART follow up data-base and medical records of the patients by using a standardized check list, which was adapted from Federal ministry Of Health HIV ART. The contents of check list include: Socio-demographic characteristics and clinical informations. Data had entered Epi data version and analyzed using SPSS version 5.3.1 and analyzed using SPSS version 20. Bivariate analysis with p-value <0.2 was done to see the association between outcome variable & independent variables. Variables with p < 0.2 in bivariate analysis were entered for multiple logistic regressions. At 95% confidence interval, explanatory variables with P <0.05 in multiple logistic regression analysis were considered as significantly association. ResultThe study found that, an overall prevalence of OIs was 62%. The finding of our study documented, from deferent HIV related OIs among patients on ART follow up at Nekemte Specialized Hospital ART clinic, the common types of OIs were; Pulmonary Tuberculosis (15.7%), Oral candidiasis (14.3%), Herpes Zoster (11.3%), Cryptococcus meningitides (5.9%), upper respiratory infection (5.8%, Persistent diarrhea (5.2%), and Extra pulmonary tuberculosis (3.8%). The occurrence of OIs on adult PLHIV patients who were with baseline WHO stage of I were 53% lower as compared to those who were with advanced baseline WHO stage of II and more {AOR: 0.468, 95 % CI (0.305-0.716). Moreover, Participants of Urban residents were 1.6 times more likely to develop OIs than those rural residents. Baseline WHO clinical staging and residence were identified as independent predictors of OIs among adult HIV infected patients. ConclusionAn overall prevalence of OIs was 62%. The prevalence of OIs is still high namely Pulmonary Tuberculosis, Oral candidiasis and Herpes Zoster are leading OIs among adult HIV infected patients. Baseline WHO clinical staging and residence were identified as independent predictors of OIs among adult HIV infected patients RecommendationsHaving skilled health professionals, early diagnosis of OIs among HIV infected patients and having equipped laboratory diagnostic setup are mandatory to be able to deal with specific diagnosis and management of OIs. Further study is recommended to determine the relationship between residence and developing OIs among HIV patients on ART follow
- organism: human
- assay: clinical cohort / trial
- research focus: host-pathogen & immune response
- approach: statistical model
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